Data/hora: 09/06/2024 11:57:27

Provedor de dados: | 31
País: | United States
Título: | A FLEXIBLE METHOD FOR EMPIRICALLY ESTIMATING PROBABILITY FUNCTIONS
Autores: | Taylor,   C. Robert.
Data: | 2003-12-30
Ano: | 1984
Palavras-chave: | Research Methods/ Statistical Methods.
Resumo: | This paper presents a hyperbolic trigonometric (HT) transformation procedure for empirically estimating a cumulative probability distribution function (cdf), from which the probability density function (pdf) can be obtained by differentiation.  Maximum likelihood (ML) is the appropriate estimation technique, but a particularly appealing feature of the HT transformation as opposed to other zero-one transformations is that the transformed cdf can be fitted with ordinary least squares (OLS) regression.  Although OLS estimates are biased and inconsistent, they are usually very close to ML estimates; thus use of OLS estimates as starting values greatly facilitates use of numerical search procedures to obtain ML estimates.  ML estimates have desirable asymptotic properties.  The procedure is no more difficult to use than unconstrained nonlinear regression.  Advantages of the procedure as compared to alternative procedures for fitting probability functions are discussed in the manuscript.  Use of the conditional method is illustrated by application to two sets of yield response data.
Tipo: | Journal Article
Idioma: | Inglês

Identificador:

12009

http://purl.umn.edu/32377

Editor: | AgEcon Search
Relação: | Western Journal of Agricultural Economics&gt;Volume 09, Number 01, July 1984

Formato:

11

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